Top AI Jobs in Denver & Boulder, CO

Lead the Registry design org end-to-end: set UX vision, KPIs, and quality standards; ship cross-platform web and mobile experiences; embed AI-native workflows; prototype and contribute production-quality interfaces; run generative and evaluative research; scale design systems; partner with PMs, engineers, and analytics; and hire, develop, and manage a high-performing team of product designers.

Design, build, test, deploy, monitor, and maintain production LLM-based agentic solutions for Commercial Customer Success. Integrate agents with CRMs and Samsara systems, define evaluation frameworks and success metrics, implement automated tests and monitoring, iterate on models and prompts, and demonstrate impact on customer outcomes and retention.

As a Staff AI Engineer, you'll lead AI product development, overseeing technical direction, system deployment, and model evaluation while collaborating across teams.

The role involves designing AI systems for mental healthcare, focusing on building scalable, production-grade systems that enhance patient engagement and clinical operations. Responsibilities include setting technical standards and ensuring safety and reliability while working with advanced AI technologies.

Build and maintain AI platform infrastructure, connectors, API integrations, and custom AI-powered applications. Implement authentication, data pipelines, and tooling to embed LLM capabilities across teams. Contribute code, documentation, reviews, and enablement while ensuring security and compliance for government requirements.

Lead cross-functional programs to transform customer support with AI-powered automation, agent tooling, analytics, and vendor evaluations. Define roadmap, size opportunities, set success metrics/OKRs, manage dependencies, and drive rollout/change management while partnering with Product, Engineering, Analytics, and Operations to deliver measurable CX improvements.

Build and lead an enterprise AI platform: design infrastructure, integrations, and custom AI applications. Own provider/tool selection, deploy production model pipelines and connectors, ensure compliance with government security requirements, mentor engineers, and deliver company-wide AI enablement and training.

Build and operate an enterprise AI platform and integrations that connect LLMs to internal systems. Develop production AI applications, manage model/provider evaluations, ensure security/compliance for government environments, and deliver company-wide AI training and enablement.

Own and improve the AI Social render pipeline and agent loops that generate on-brand Instagram carousels and reels. Build prompts, structured outputs, tool-calling, and media composition to ship high-quality generative image, video, voice, and music products in collaboration with product, design, and content strategy.

Build and operate Coinbase's LLM and agent platform: unified model gateway, AI Hub, secure microVM agent runtime, knowledge base integrations, AI FinOps, observability and evaluation tooling, and production-grade agent deployments with teams across the company.

Manage, coach, and develop a team of 10–12 BDRs to hit activity, pipeline, and quota targets. Build and standardize BDR motions with Marketing and Sales, own hiring/onboarding/ramp, report performance, and partner cross-functionally to translate field insights into campaigns. Drive data-informed coaching and performance management to generate pipeline and revenue.

Maintain and update EchoStar's Data & AI Governance Compliance and Risk Register, translate AI regulations into controls, coordinate evidence for audits, integrate compliance gates into CI/CD and MLOps, produce executive compliance reporting, and oversee AI risk assessments.

Lead deployment and operationalization of AI and automation across Global Media Operations. Identify use cases, translate requirements, manage end-to-end delivery, drive rollout (SOPs, training, adoption), partner with Product/Engineering and vendors, and align solutions with enterprise AI governance and business priorities.

Lead and build Deepgram's AI enablement function: prototype and ship reusable agents, MCP servers, paved-road workflows, prompt and retrieval patterns, and an enablement hub. Drive company-wide AI adoption with measurable productivity metrics, embed safe-use guardrails, partner across Platform, Security, Data, and People Ops, and grow a central team and distributed champions network.

Lead end-to-end delivery of ML infrastructure and AI tooling programs, defining architecture and rollout strategies for training, serving, and monitoring. Coordinate research, engineering, product, and data teams to optimize inference cost/latency, build internal tools for experiment tracking and model versioning, and resolve bottlenecks to enable faster, scalable ML deployments.

Design, build, and operate agentic AI systems end-to-end for Professional Services. Translate stakeholder needs into secure, scalable multi-agent architectures, define performance benchmarks, manage deployments and incident response, advise leadership, mentor teammates, and maintain runbooks and production tooling including on-call responsibilities.

Scale and secure the enterprise Databricks platform on AWS for production analytics, ML, and AI agent workloads. Administer workspaces, Unity Catalog governance, CI/CD pipelines, Terraform automation, MCP server integration for agent frameworks, cluster policy enforcement, cost attribution, monitoring, incident response, and mentor junior engineers.

Lead or support integration and testing of spacecraft hardware in lab and cleanroom environments. Create AI&T flows, develop and execute test procedures, use test and measurement equipment and GSE, document results, identify risks and facilities needs, and coordinate with systems engineers and external partners during spacecraft acceptance and launch operations.

Lead and execute spacecraft assembly, integration, and test (AI&T) campaigns; define test strategies and AI&T flows; manage facilities, GSE, cost/schedule estimates; author proposals; mentor engineers and technicians; ensure quality, risk mitigation, and operational success in cleanroom and lab environments.

Lead and scale GM's enterprise Privacy and AI governance operations: build workflows, training, metrics, reporting, and documentation; operationalize AI impact assessments and governance platform; drive continuous improvement, automation, and cross-functional stakeholder alignment to strengthen privacy and responsible AI program maturity.

Design and build AI-powered prototypes and end-to-end workflows using LLMs to solve creative and operational problems. Partner with Services leaders to prioritize opportunities, translate ideas into roadmaps, enable adoption through documentation and training, and collaborate with engineering to productionize solutions.

The Applied AI Scientist III develops advanced analytics solutions utilizing AI technologies, leading projects in predictive analytics and NLP to enhance healthcare operations and patient care.

Lead design and scaling of a unified fraud and risk platform. Own roadmap, fraud metrics, SQL-based analysis, A/B testing, real-time detection models, and cross-functional delivery to balance customer experience and risk mitigation.

The Principal of Solution Engineering leads pre-sales efforts, designs digital healthcare experiences using League's platform, and collaborates across teams to deliver AI-driven solutions while ensuring compliance with security policies.

The Data & Analytics team at Surescripts transforms healthcare data into actionable insights, collaborating with various stakeholders to support critical decisions across the healthcare ecosystem.